| Registro completo |
| Provedor de dados: |
AgEcon
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| País: |
United States
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| Título: |
Optimizing Voluntary Deforestation Policy in the Face of Adverse Selection and Costly Transfers
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| Autores: |
van Benthem, Arthur A.
Kerr, Suzi
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| Data: |
2010-11-18
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| Ano: |
2010
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| Palavras-chave: |
Voluntary opt-in
Adverse selection
Deforestation
Offsets
Emissions trading
REDD
Agricultural and Food Policy
Community/Rural/Urban Development
Environmental Economics and Policy
Land Economics/Use
Q54
Q56
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| Resumo: |
As part of international climate change policy, voluntary opt-in programs to reduce emissions in unregulated sectors or countries have spurred considerable discussion. Since any regulator will make errors in predicting baselines, adverse selection will reduce efficiency since participants will self-select into the program. In contrast, pure subsidies lead to full participation but require large financial transfers; this is a particular challenge across countries. A global social planner facing costless transfers would choose such a subsidy to maximize efficiency. However, any actual policy needs to be individually rational for both the buying (industrialized) and selling (developing) country. We present a simple model to analyze this trade-off between adverse selection and infra-marginal transfers. The model leads to the following findings. First, extending the scale of voluntary programs both improves efficiency and reduces transfers. Second, the set of individually rational and Pareto efficient policies typically features a combination of credit discounting and stringent assigned baselines which reduce efficiency. Third, if the industrialized countries can be persuaded to be more generous, the feasible policy set can come close to the globally efficient policy to avoid deforestation.
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| Tipo: |
Conference Paper or Presentation
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| Idioma: |
Inglês
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| Identificador: |
http://purl.umn.edu/96813
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| Relação: |
New Zealand Agricultural and Resource Economics Society>2010 Conference, August 26-27, 2010, Nelson, New Zealand
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| Formato: |
48
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